The day-to-day collaboration between the researchers in Public Health and Biostatistics at the School reveals unified topics that cut across many applications. This series of presentations introduces the topics that show empirically to be most important in these collaborations; and emphasizes concepts over details, through recent applications in Public Health.

The Art of the Probable" addresses the history of scientific ideas, in particular the emergence and development of mathematical probability. But it is neither meant to be a history of the exact sciences per se nor an annex to, say, the Course 6 curriculum in probability and statistics. Rather, our objective is to focus on the formal, thematic, and rhetorical features that imaginative literature shares with texts in the history of probability. These shared issues include (but are not limited to): the attempt to quantify or otherwise explain the presence of chance, risk, and contingency in everyday life; the deduction of causes for phenomena that are knowable only in their effects; and, above all, the question of what it means to think and act rationally in an uncertain world. Our course therefore aims to broaden students’ appreciation for and understanding of how literature interacts with--both reflecting upon and contributing to--the scientific understanding of the world. We are just as centrally committed to encouraging students to regard imaginative literature as a unique contribution to knowledge in its own right, and to see literary works of art as objects that demand and richly repay close critical analysis. It is our hope that the course will serve students well if they elect to pursue further work in Literature or other discipline in SHASS, and also enrich or complement their understanding of probability and statistics in other scientific and engineering subjects they elect to take.

Dr. Chris Muhlstein explains that researchers learn about the scientific basis for failure of materials by running experiments in the lab, using a simple shape like a glass rod to calculate the strength of material and predict its failure. The same tests can be done at the micro and nano scale using tiny specimens. Students can run a similar experiment with a bar of chocolate.

This course addresses the challenges of defining a relationship between exposure to environmental chemicals and human disease. Course topics include epidemiological approaches to understanding disease causation; biostatistical methods; evaluation of human exposure to chemicals, and their internal distribution, metabolism, reactions with cellular components, and biological effects; and qualitative and quantitative health risk assessment methods used in the U.S. as bases for regulatory decision-making. Throughout the term, students consider case studies of local and national interest.

" Explore the future through modeling, reading, and discussion in an open-ended seminar! Our fields of interest will include changes in science and technology, culture and lifestyles, and dominant paradigms and societies."

This module focuses on the solar wind information obtained by NASA-s Genesis spacecraft. Genesis collects pristine solar wind material -ionic particles from the Sun- that will provide clues about the elemental composition of the original solar nebula.

This lab introduces basic chemistry concepts in molecular interactions, measurements, prediction, and critical thinking.

This video segment adapted from NOVA tells the tragic story of two Japanese seismologists who disagreed about the threat of earthquakes in the early twentieth century. Today, seismologists in California offer residents a probability of risk that an earthquake might occur.

Introduces the theory and application of modern, computationally-based methods for exploring and drawing inferences from data. Covers re-sampling methods, non-parametric regression, prediction, and dimension reduction and clustering. Specific topics include Monte Carlo simulation, bootstrap cross-validation, splines, local weighted regression, CART, random forests, neural networks, support vector machines, and hierarchical clustering. De-emphasizes proofs and replaces them with extended discussion of interpretation of results and simulation and data analysis for illustration.

The following lesson will enable students to develop tactile and auditory patterns. As students observe, analyze, and make predictions about patterns they will enhance their problem-solving and reasoning skills.

In this unit, students will be focusing on determining importance; summarizing; making predictions; recognizing plot structure; and identifying flashbacks and foreshadowing. Wherever possible, mini-lesson texts relate to American life in the 1930s, and all students will be reading literature circle novels set during this time period in American history.

Students review geometric terms by making predictions about what the Greedy Triangle will become as the teacher reads the book, "The Greedy Triangle". Students will create geometric creatures after the review.

This team-taught subject is for doctoral students working on emerging technologies at the interface of technology, policy and societal issues. It integrates concepts of research strategy and design from a variety of disciplines. The class addresses problem identification and formulation of research topics, the role of qualitative and quantitative research methods, and the use of various data collection techniques. Coursework focuses on students' thesis proposals, faculty-student study panels, critical evaluation of research design, and ethical issues in conducting research and gathering data.

The students will be following an integrated unit on "Helping." They will use reading, math, Social Sciences, science, technology, and other areas of study. Students will read, as a group, the book The Little Yellow Chicken by Joy Cowley. The students will be incorporating prediction, prior knowledge, comprehension skills, and language skills for the word family "-ook", the vowel sound "e", and the exclamation mark. The technology to be utilized by the students consists of use of the HyperStudio for math review, Math Software, Graph Club to create a graph of favorite party foods, Inspiration to guide and create graphic organizers for writing, and the Ultimate Writing Machine to create their own version of The Little Yellow Chicken. They will also incorporate color words to practice the Spanish Language.

A lot of events in our life seem random or impossible to predict. However, with probability theory we can learn more about these things to solve interesting problems that range from the lottery to diagnosing medical diseases. By teaching you basic principles and more advanced topics about theorems and models, this class will give you the tools to see the world in a different way that may not be intuitive but is proved by the math behind it.

Highlight the meaning of a function, and see how it can be seen as something changing over time, with this tool that links a motion model to a graph.

Focus on multivariate data analysis procedures, emphasizing regression. Considers model specification, autocorrelation, instrumental variables, and causal modelling. Students must have taken at least one previous subject in statistics. Open to qualified undergraduates. Course home page description: This course is the second semester in the statistics sequence for political science and public policy offered in the Political Science Department at MIT. The intellectual thrust of the course is a presentation of statistical models for estimating causal effects of variables. The model of an effect is a conditional mean (though we might imagine other effect). The notion of causality is the effect of one variable on another holding all else constant.

Students will use a TI82 or TI83 calculator to construct a scatterplot, find the equation of the least-squares regression line for a set of data, find the coefficient of determination, and make predictions by using the line.

Children will work in groups using spinners with 4 colors to make predictions about probability, gather and record data, and make conclusions about outcome.